Investigating future climate change impacts on streamflow and drought characterization in the Arno River basin, Tuscany, Italy, using CMIP6 and SWAT+ modelling
Abstract
Assessing future climate change impacts is essential for developing adaptive water resource management strategies in river basins. This study presents an integrated modeling framework combining the Soil and Water Assessment Tool (SWAT+) hydrological model with bias-corrected CMIP6 climate projections to assess hydroclimatic changes and drought propagation in the Arno River basin, Tuscany, Italy. We employed five General Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under Shared Socioeconomic Pathways SSP2-4.5 and SSP5-8.5, Quantile Delta Mapping (QDM) bias correction, and Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) drought indices to examine climate extremes spanning from 2015 to 2100. Results demonstrate: (1) pronounced warming trends with temperature increases of 3°C under SSP2-4.5 and 5°C under SSP5-8.5 by century's end; (2) declining precipitation trends at rates of –0.51 mm year -1 and –1.77 mm year -1 for moderate and high emission pathways respectively; (3) streamflow reductions of –0.07 m 3 s -1 year -1 and –0.19 m 3 s -1 year -1 under SSP2-4.5 and SSP5-8.5 scenarios; and (4) increasing drought severity with total drought duration reaching 99 months for meteorological droughts and 106 months for hydrological droughts under high-emission pathways, compared to historical baselines of 41 and 32 months respectively. Strong correlations (r = 0.80–0.95) between meteorological and hydrological drought indices demonstrate robust drought propagation from precipitation deficits to streamflow reductions. This study provides crucial understanding of hydroclimatic changes, enabling policymakers and water managers to develop resilient strategies for the Arno River basin.
Fields of Study & Subjects
Hydrology and Watershed Management Studies
Hydrology and Drought Analysis
Climate variability and models
Publication details
- Journal / source
- Water Cycle
- Publisher
- Elsevier BV
- Volume
- 7
- Pages
- 554–572
- Publication date
- 1 January 2026
- Language
- EN